Our new paper (lead author Xinyuan Huang, a Ph.D student in Civil Engineering at Penn State, and co-authored with Jonathan Lamontagne, Klaus Keller, and Wei Peng) was just published in Nature Sustainability, along with a News & Views on the paper by Noelle E. Selin. An open access version is also available.

In this paper, we couple a large-scale integrated assessment model (IAM), the Global Change Analysis Model, to a reduced-form atmospheric transport and air quality model. The simplified air quality model allows us to systematically explore relevant uncertainties using a large ensemble of future states of the world, reflecting around 15,000 different combinations of socioeconomic, technical, and agricultural trajectories. This allows us to represent many of the relevant deep uncertainties in future climate outcomes. We look at the impacts of a relatively modest global carbon tax on air quality across these states of the world as a proxy for a variety of different climate mitigation policies.

Our key findings are:

  • There are clear air quality co-benefits in most of the world, particularly China and India, from the replacement of coal with cleaner sources of electricity generation. This is a robust finding, albeit one which is expected.
  • The specifics of land use changes play a major role in whether climate mitigation can result in negative outcomes. In many states of the world, a major effect of the carbon tax is the expansion of biofuel production (this is common in current IAMs). Creating the extra agricultural land for this biofuel can lead to large-scale deforestration in many countries, including Canada, Russia, and the United States. Under the default model configuration, this can result in co-harms from the generation of organic carbon, linked to deforestation from burning, particularly for countries with relatively high levels of air quality due to ongoing electric power system transitions. These co-harms tend to disappear when we use emissions factors for deforestation which are more appropriate for clear-cutting.
  • Socio-demographics (particularly age of the exposed population) can play a large role in vulnerability to negative air quality effects.

This work was funded by the National Science Foundation, under grant number 2125293, and seed grant support was provided by the Penn State Institute for Energy and the Environment and Institute for Computational and Data Sciences.